36 jobs found

Kroo Ltd is seeking a Data Scientist to enhance its banking capabilities through advanced analytics and data science. As part of a hybrid working model, you will collaborate with various teams to build models that help improve decision-making in areas such as credit risk and fraud prevention. The ideal candidate will have experience in statistical modeling, strong analytical skills, and proficiency in Python and SQL. Join Kroo to help shape the future of banking!

Kroo Bank is charting the future of banking through technology, data, and innovation. As a digital first bank, we use data science to help us make smarter decisions, improve customer outcomes, and build products that customers trust and love. The rapid pace of change within fintech creates exciting opportunities to apply advanced analytics, machine learning, and experimentation to real business challenges. As a Data Scientist, you will play a key role in helping Kroo use data more effectively across a wide range of business areas, partnering with teams across Product, Risk, Operations, Compliance, and Engineering. This role is responsible for building, evaluating, and deploying data science solutions that support strategic decision making and improve customer experiences. You will work on high impact initiatives across areas such as credit risk, fraud prevention, customer engagement, and operational efficiency, helping the business make informed decisions through robust analysis, experimentation, and modelling. How you'll contribute: Build and iterate on statistical and machine learning models to solve business problems across areas such as credit risk, fraud, customer engagement, and operational efficiency. Partner with stakeholders to define problem statements, success metrics, data requirements, and practical implementation plans. Conduct data exploration and feature engineering to uncover drivers of outcomes and improve model performance and interpretability. Develop robust evaluation frameworks, including appropriate baselines, validation strategies, monitoring metrics, and model performance reporting. Support deployment of models into production in collaboration with Engineering, contributing to reproducible pipelines and model documentation. Monitor models in production, identify performance drift, propose improvements, and support ongoing recalibration or retraining where required. Apply probability and statistical inference to design experiments, interpret results, and provide clear recommendations to stakeholders. Contribute to high quality data practices by identifying data quality issues, supporting cleaning and normalisation approaches, and defining standards for reliable datasets. Write maintainable, well tested Python code using common data science libraries, and follow engineering best practices appropriate for production systems. Use SQL and dbt to extract, transform, and validate data for analysis and modelling, ensuring traceability and reliability of outputs. Collaborate with Risk, Compliance, and Audit stakeholders to ensure data science work is appropriately governed, documented, and aligned with regulatory expectations. Support continuous improvement across data science methodologies, tooling, and ways of working. Required skills and behaviours: Experience building and evaluating statistical and machine learning models in a commercial environment. Strong analytical and problem solving skills with the ability to translate business challenges into practical data science solutions. Ability to conduct basic data collection by independently sourcing and defining required datasets, partnering with stakeholders to clarify data needs and ensure appropriate coverage and traceability. Ability to perform data cleaning effectively by independently applying robust cleaning approaches, proactively identifying data quality issues, and contributing to improving data reliability and standards. Ability to conduct basic data analysis by independently performing exploratory analysis and statistical investigation, translating findings into clear insights and actionable recommendations. Strong programming fundamentals with experience writing maintainable Python code for analysis and modelling, contributing to shared codebases through good practices, testing, and documentation. Experience using SQL and dbt to extract, transform, validate, and analyse data. Ability to apply visualisation techniques to produce clear, purposeful visualisations and model performance summaries that support decision making across technical and non technical audiences. Ability to communicate effectively by explaining complex analytical concepts clearly and tailoring messages to a wide range of stakeholders. Strong attention to detail, ensuring outputs are validated, reproducible, and documented in line with governance and compliance requirements. Ability to manage data projects proficiently by planning and delivering work to agreed timelines, managing competing priorities, and contributing positively to team delivery processes. Experience working collaboratively with Product, Risk, Operations, Compliance, and Engineering teams is beneficial. Awareness of model governance, risk management, and regulatory considerations within a financial services environment is advantageous. Hybrid Working At Kroo Bank, we have a hybrid/ flexible policy that gives both individuals and teams a lot of freedom when it comes to using the office space to boost productivity. Our London office is a great resource to collaborate and candidates should be able to attend 1-2 days per week regularly to align with how we work at the moment. Diversity and Inclusion We wholeheartedly uphold our commitment to fostering a diverse and inclusive workplace. Every employee is highly regarded, respected, and supported without any form of judgement or prejudice. We consider Diversity, Equality, and Inclusion as fundamental pillars guiding our path in all aspects of our bank. We also ensure that reasonable adjustments are made available to all candidates throughout the recruitment process.

Salary: £70,000 - 100,000 per year Requirements A 1st class or 2:1 degree in Computer Science or a STEM subject from a top-ranked university 3+ years of experience in Python development Strong experience with Python, FastAPI, Pydantic, PostgreSQL, and AWS Experience with DevOps tools such as Kubernetes, Docker, Terraform, and Jenkins Very strong software engineering principles Enthusiasm for a startup environment and cross-functional teams Passion for automation and data infrastructure Responsibilities Contribute to the design, development, and delivery of scalable, high-impact features across our platform Work closely with experienced engineers, product managers, and data scientists to build reliable systems that solve complex financial problems Help build next-generation tools for funding and working capital optimisation Develop secure, scalable, and smart financial technology solutions from the ground up Take ownership of individual projects and help drive meaningful product outcomes Technologies AWS DevOps Docker FastAPI Jenkins Kubernetes PostgreSQL Python Terraform Cloud More We are a fintech company building next-generation tools that help companies get funding and optimise their working capital. We are changing how corporate finance works by replacing static, limited, and often stale financial metrics with live, data-driven insights sourced from direct connections to our clients systems. You will join a strong team of Python engineers, data scientists, and financial experts who are building scalable, secure, and smart financial tools. This role offers an excellent opportunity to deepen your technical expertise, take ownership of individual projects, and grow in a supportive, fast-paced startup environment. last updated 25 week of 2026

What we're looking for Are you curious about how things work and motivated by uncovering insights hidden in data? As a Data Analyst at ARQ, you'll help us understand our business, customers, and operations through rigorous analysis and thoughtful storytelling. You'll explore data, detect patterns, and build the foundations for decisions that shape the future of our products and company. This is a role for someone early in their analytics career who wants to grow - learning how data drives product, financial, and strategic decisions in a fast paced fintech environment. What you'll be doing Explore and Analyze Data: Investigate user behavior, performance trends, and key metrics to uncover what's driving changes. Identify Anomalies and Opportunities: Spot unusual patterns or spikes and help the team understand their root causes. Reporting & Automation: Build and maintain dashboards and automated reports that make data accessible and reliable. Decision Support: Translate analytical findings into clear recommendations for product and operational improvements. Metric Design: Help define and refine the KPIs that matter most for our business and customer experience. Documentation: Keep analyses, methodologies, and assumptions well documented and reproducible. Modeling & Experimentation: Contribute to basic modeling tasks and structured experiments under guidance from senior analysts or data scientists. Continuous Learning: Expand your analytical toolkit and develop product sense through real world problem solving and mentorship. What you'll need 1-3 years of experience in analytics, data, or operations (internships count) Strong SQL skills for querying and exploring datasets Analytical curiosity and a structured approach to problem solving Good communication skills - able to explain insights clearly and visually Initiative to automate repetitive tasks and improve reporting workflows Interest in fintech, data driven decision making, and machine learning concepts (Bonus) Familiarity with Python for basic data manipulation (Bonus) Spanish/Portuguese proficiency for internal and external communications Nice to have Experience with BI or visualization tools (Metabase, Looker, Power BI, etc.) Understanding of key business metrics and experimentation principles Exposure to fraud, financial, or product analytics (any domain welcome) Benefits Competitive salary Sign on stock options bonus, so you become part of the success of the company Discretionary performance bonus (stock options) Paid annual leave Latest technology to work with Autonomy and ownership from day one Strong team that will help you improve your skills

About the Role We're hiring a mid-level Data Scientist (2 to 5 years' experience) for our Data team, working within Risk & Fraud. The brief is simple: reduce fraud without adding friction for good users. In practice that means ML models, deterministic rules and signal tuning, and working directly with our external risk vendors. You own that work end to end, from the question, to what ships, to the decision leadership makes off the back of it. Risk and fraud is where you'll have the clearest impact, but the role reaches across Product, Growth, and Engineering, and your work turns into product, policy, and revenue. If you're drawn to crypto, payments, and the kind of data they throw off, there's a lot here to get into. What You'll Do Risk, fraud and compliance. Build and iterate on fraud detection, chargeback prediction, and transaction-risk models. Develop features and rule sets that work alongside our Risk and Compliance teams to keep bad actors out without adding friction for good users. Product analytics and growth. Own funnel analytics across on-ramp and off-ramp flows. Design and analyze A/B and multivariate experiments, identify conversion bottlenecks (KYC, payment method, geo), and partner with PMs and designers to ship measurable improvements. ML/AI modeling. Design, train, and deploy machine learning models, from classification and forecasting to clustering and recommendation, that power decisions inside the product (e.g., dynamic payment method ranking, user lifetime value, churn prediction). Business intelligence and reporting. Build trusted dashboards and self-serve data products for Product, Growth, Finance, and the executive team. Define and steward the metrics that the business runs on. Storytelling and strategy. Turn analyses into clear narratives and recommendations. Present findings to engineers, PMs, and the C-suite alike, and influence roadmaps with data. Data craftsmanship. Partner with Data Engineering to improve event tracking, data models, and the warehouse. Treat data quality as a first-class product. Requirements: 2 to 5 years of experience as a data scientist, analytics engineer, or quantitative analyst, ideally at a fintech, payments, marketplace, or consumer tech company. Strong SQL. You can navigate large, messy warehouses (BigQuery, Snowflake, Redshift, or similar) and write performant, readable queries. Solid Python (or R) for analysis and modeling: pandas, scikit-learn, statsmodels, and at least one deep-learning or gradient-boosting framework (XGBoost, LightGBM, PyTorch, TensorFlow). Experimentation fluency. You understand the math behind A/B testing, sample sizing, power, and common pitfalls (peeking, multiple comparisons, novelty effects). Machine learning intuition. You can pick the right model for the problem, evaluate it honestly (precision/recall trade-offs, calibration, drift), and ship it responsibly. Visualization and BI. Comfortable building dashboards in Looker, Metabase, Tableau, Superset, or similar. Communication. You can explain a confusion matrix to a PM and a funnel drop-off to the CEO, in the same week, in the same tone. Ownership. You treat ambiguous problems as opportunities and don't wait to be told what to analyze next. Nice to Have Experience in crypto, payments, banking, fraud, or compliance. Familiarity with dbt, Airflow, or similar data-stack tooling. Exposure to causal inference (difference-in-differences, propensity scoring, uplift modeling). Experience deploying models to production (batch or real-time) alongside engineers. Knowledge of AML / KYC frameworks or experience working with regulators.

Starling is the UK's first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way. We're a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We're a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices. Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together! The way to thrive and shine within Starling is to be a self driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness. Hybrid Working We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. Our Data Environment Our Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering. Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers. Hear from the team in our latest blogs or our case studies with Women in Tech. About the Role The ML Projects team is at the forefront of bringing cutting edge machine learning to the core of what we do at Starling. As a software engineer on the ML Projects team you will work with other engineers and data scientists to design, implement and maintain features that make use of machine learning models under the hood. This could mean anything from creating a brand new ML powered feature from scratch to seamlessly integrating a new model into our core banking platform. You might find yourself designing robust infrastructure and pipelines or discovering a completely new approach to a complex problem. We believe in empowering our engineers to take ownership and drive solutions from ideation to launch. This means you'll have the autonomy to shape your own path, identify challenges, and collaborate with colleagues across teams to deliver impactful solutions across a range of technologies. We're looking for a skilled software engineer who thrives on building and scaling complex systems. You should have a proven track record of delivering robust, multi technology applications within an enterprise environment. We're open minded when it comes to hiring and we care more about aptitude and attitude than specific qualifications. We are very open about how we deliver software. We believe in clean coding, simple solutions, automated testing and continuous deployment. If you care enough to find elegant solutions to difficult technical problems, we'd love to hear from you. Tech Stack Python Java, which makes up the majority of our backend codebase JavaScript, particularly React, which makes up our frontend Postgres and SQL AWS & GCP - we're cloud native TeamCity for CI / CD (lots of teams are releasing code 15-20 times per day!) Terraform Prometheus and Grafana If you have built and deployed complex Python applications or have hands on experience with generative AI and LLMs, we would be especially keen to talk. We are moving fast in the AI space and want people who are excited to help us define what comes next. Interview Process Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team: Stage 1 - 45 mins with one of the team Stage 2 - Take home challenge Stage 3 - 90 mins technical interview with two team members Stage 4 - 45 min final with two executives Benefits 33 days holiday (including public holidays, which you can take when it works best for you) An extra day's holiday for your birthday Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off 16 hours paid volunteering time a year Salary sacrifice, company enhanced pension scheme Life insurance at 4x your salary & group income protection Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr & Mrs Smith and Peloton Generous family friendly policies Incentives refer a friend scheme Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing About Us You may be put off applying for a role because you don't tick every box. Forget that! While we can't accommodate every flexible working request, we're always open to discussion. So, if you're excited about working with us, but aren't sure if you're 100% there yet, get in touch anyway. We're on a mission to radically reshape banking - and that starts with our brilliant team. Whatever came before, we're proud to bring together people of all backgrounds and experiences who love working together to solve problems. Equal Opportunity Employer Starling Bank is an equal opportunity employer, and we're proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Starling Bank are considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.

About the Role We're hiring a mid-level Data Scientist (2 to 5 years' experience) for our Data team, working within Risk & Fraud. The brief is simple: reduce fraud without adding friction for good users. In practice that means ML models, deterministic rules and signal tuning, and working directly with our external risk vendors. You own that work end to end, from the question, to what ships, to the decision leadership makes off the back of it. Risk and fraud is where you'll have the clearest impact, but the role reaches across Product, Growth, and Engineering, and your work turns into product, policy, and revenue. If you're drawn to crypto, payments, and the kind of data they throw off, there's a lot here to get into. What You'll Do Risk, fraud and compliance. Build and iterate on fraud detection, chargeback prediction, and transaction-risk models. Develop features and rule sets that work alongside our Risk and Compliance teams to keep bad actors out without adding friction for good users. Product analytics and growth. Own funnel analytics across on-ramp and off-ramp flows. Design and analyze A/B and multivariate experiments, identify conversion bottlenecks (KYC, payment method, geo), and partner with PMs and designers to ship measurable improvements. ML/AI modeling. Design, train, and deploy machine learning models, from classification and forecasting to clustering and recommendation, that power decisions inside the product (e.g., dynamic payment method ranking, user lifetime value, churn prediction). Business intelligence and reporting. Build trusted dashboards and self-serve data products for Product, Growth, Finance, and the executive team. Define and steward the metrics that the business runs on. Storytelling and strategy. Turn analyses into clear narratives and recommendations. Present findings to engineers, PMs, and the C-suite alike, and influence roadmaps with data. Data craftsmanship. Partner with Data Engineering to improve event tracking, data models, and the warehouse. Treat data quality as a first-class product. Requirements: 2 to 5 years of experience as a data scientist, analytics engineer, or quantitative analyst, ideally at a fintech, payments, marketplace, or consumer tech company. Strong SQL. You can navigate large, messy warehouses (BigQuery, Snowflake, Redshift, or similar) and write performant, readable queries. Solid Python (or R) for analysis and modeling: pandas, scikit-learn, statsmodels, and at least one deep-learning or gradient-boosting framework (XGBoost, LightGBM, PyTorch, TensorFlow). Experimentation fluency. You understand the math behind A/B testing, sample sizing, power, and common pitfalls (peeking, multiple comparisons, novelty effects). Machine learning intuition. You can pick the right model for the problem, evaluate it honestly (precision/recall trade-offs, calibration, drift), and ship it responsibly. Visualization and BI. Comfortable building dashboards in Looker, Metabase, Tableau, Superset, or similar. Communication. You can explain a confusion matrix to a PM and a funnel drop-off to the CEO, in the same week, in the same tone. Ownership. You treat ambiguous problems as opportunities and don't wait to be told what to analyze next. Nice to Have Experience in crypto, payments, banking, fraud, or compliance. Familiarity with dbt, Airflow, or similar data-stack tooling. Exposure to causal inference (difference-in-differences, propensity scoring, uplift modeling). Experience deploying models to production (batch or real-time) alongside engineers. Knowledge of AML / KYC frameworks or experience working with regulators.

We're looking for a Data Scientist who loves building predictive models and solving ambiguous data problems. You'll own the models that shape loan eligibility and pricing across 5 African markets. This is a small team with big responsibility, where your work directly shapes lending strategy for millions of customers. Impact Your models will directly shape how millions of underserved customers access credit for the first time. We've already helped over 7 million customers access over $2 billion in credit - and we process over 1.5 million payments daily. It's your chance to be part of something that's literally transforming lives across an entire continent Opportunity Mission-driven data science: Build credit scoring and pricing models that expand financial access for customers traditionally excluded from formal lending Global recognition: Join a company named by TIME 100 as one of the world's most influential and by the Financial Times as Africa's fastest-growing for 4 consecutive years () Scale challenges: Work with rich repayment datasets across 5 African markets, developing ML models that balance growth with credit risk at scale Environmental impact: We're carbon-negative, having displaced over 2.1 million tonnes of emissions What You'll Do At M KOPA, you'll build and refine the predictive models that power our lending strategy. You'll sit within a small, high performing team with end to end ownership of credit scoring, loan eligibility, and pricing optimisation - working cross functionally with engineers, analysts, growth managers, and commercial stakeholders across multiple countries. Join us in combining cutting edge data science with purpose driven work that makes digital and financial inclusion possible across Africa. Day to day, you'll be: Building and refining credit scoring models that assess customer creditworthiness, default risk, and loan pricing across multiple markets Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact Collaborating cross functionally with engineers, data scientists, and commercial stakeholders to scale models into production Technical Environment Languages & Libraries: Python, SQL, scikit learn, pandas, numpy, and relevant ML libraries Techniques: Predictive modelling, classification/regression, feature engineering, model selection, hyperparameter tuning, A/B testing Domain: Credit scoring, underwriting, loan pricing, risk analytics Our Team Approach Low ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact High degree of ownership over your domain - you're empowered to make data driven decisions and prioritise solutions Cross functional collaboration with engineering, product, and commercial teams across multiple countries Analytical rigour combined with deep market understanding to serve customers excluded from formal financial services What You Need Credit accessibility and affordability are at the core of this role. You'll join a small, high performing team where every day brings new modelling challenges and analyses that shape our lending strategy. If building models that can transform financial access for millions of African customers excites you, we'd love to hear from you. Required Experience Experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems ML background with hands on experience in model development, validation, deployment, and performance monitoring Proficiency in Python, SQL, and relevant ML libraries (scikit learn, pandas, numpy, etc.) with experience in feature engineering, model selection, and hyperparameter tuning Experience translating complex model outputs into actionable business strategies and stakeholder communications Ability to work cross functionally with product, engineering, and commercial teams Strong data communication skills - written, oral, and visual Highly Desirable Experience in credit, underwriting, lending analytics, or fintech modelling Location & Benefits Fully remote role within UTC -1 to UTC +3 time zones Work with diverse teams across UK, Europe, and Africa Professional development programmes and coaching partnerships Family friendly policies and flexible working arrangements Well being support and career growth opportunities Our Mission We make financing for everyday essentials accessible to everyone. We strive to drive greater inclusion of women, youth, and low income communities. Our Impact Our technology has created measurable change: Connected : 2.5 million first time smartphone users connected Prosperous : 70% of customers use M KOPA products for income generation, with 35,000 livelihoods created for agents Green : 2.1 million tonnes of CO avoided through clean energy products, with over 127,700 circular economy products provided Ready to build models that create real world financial inclusion while advancing your career in data science? Apply now. Why M KOPA? At M KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on the job training. We support individual journeys with family friendly policies, prioritise well being, and embrace flexibility. Join us in shaping the future of M KOPA as we grow together. Explore more at Recognized four times by the Financial Times as one Africa's fastest growing companies (2022, 2023, 2024 and 2025) and by TIME100 Most influential companies in the world 2023 and 2024, we've served over 6 million customers, unlocking $1.5 billion in cumulative credit for the unbanked across Africa. Important Notice M KOPA is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained staff. Women, minorities, and people with disabilities are strongly encouraged to apply. M KOPA explicitly prohibits the use of forced or child labour and respects the rights of its employees to agree to terms and conditions of employment voluntarily, without coercion, and freely terminate their employment on appropriate notice. M KOPA shall ensure that its employees are of legal working age and shall comply with local laws for youth employment or student work, such as internships or apprenticeships. M KOPA does not collect or charge any money as a pre employment or post employment requirement. This means we never ask for 'recruitment fees', 'processing fees', 'interview fees', or any other kind of money in exchange for offer letters or interviews at any time during the hiring process. Applications for this position will be reviewed on a rolling basis. Shortlisting and interviews will take place at any stage during the recruitment process. We reserve the right to close the vacancy early if a suitable candidate is selected before the advertised closing date. If your application is successful M KOPA undertakes pre employment background checks as part of its recruitment process, these include criminal records, identification verification, academic qualifications, employment dates and employer references.

Junior Data Scientist High-Growth FinTech A fast-scaling FinTech is looking for a Data Scientist to join an ambitious team and work with large, complex datasets to build models that improve pricing, risk assessment, customer experience, and business performance. This is an exceptional opportunity to accelerate your career in a collaborative environment where you'll work alongside experienced engineers and data specialists while making a real impact from day one. About the Role Develop models and analytical solutions that influence key business decisions. Work across a variety of challenges including forecasting, optimisation, risk, and customer insights. Build, test, and deploy machine learning models into production. Partner with Product, Engineering, and Commercial teams to deliver data-driven solutions. Contribute to the evolution of a modern data platform and best practices across the business. About You Strong Python skills and familiarity with common data science libraries. Understanding of machine learning, statistics, and experimentation. Experience with SQL and modern data tools is beneficial. Curious, commercially minded, and excited by solving real-world problems. A collaborative communicator who enjoys working across teams. Ambitious and eager to grow quickly in a supportive, high-performing culture. Join a company where you'll be trusted early, learn from exceptional teammates, and build a career in one of the most exciting environments in FinTech.

Position Type: Full time Type Of Hire: Experienced (relevant combo of work and education) Education Desired: Associate's Degree At FIS, our technology and our people are moving forward. We advance the way the world pays, banks and invests. We believe in building inclusive, diverse teams. Together, we innovate to help our colleagues, clients and communities succeed. If you're ready to grow your career and make an impact in fintech, we have one question: Are you FIS? About the role Are you ready to shape the future of AI within one of the world's most influential fintech companies? At FIS, we're hiring an experienced Engineer Principal, Artificial Intelligence / Machine Learning to define, lead, and execute our enterprise wide AI/ML vision. In this strategic and highly visible role, you will architect and drive cutting edge AI systems that power transformation across our global commercial organization. You'll lead the design and development of advanced machine learning algorithms, intelligent agents, and enterprise scale AI platforms-solving complex challenges unique to fintech. You will work closely with cross functional teams-including product managers, software engineers, data scientists, and business leaders-to build and embed AI solutions into FIS products, tools, and processes. You'll also shape how the entire commercial organization interacts with AI through modern architectures and next generation agentic systems. What you will be doing Providing strategic leadership and owning the AI/ML roadmap for the commercial organization. Leading and growing a high calibre team of Data Scientists and AI/ML engineers, fostering a culture of innovation, collaboration, and continuous learning. Designing, building, and deploying AI Agents at scale-from automated lead generation agents to intelligent pricing and decisioning systems. Developing advanced ML models and agentic systems to address complex challenges across fintech, including predictive analytics, optimization, personalization, and intelligent automation. Owning the strategy and architecture for how the entire commercial organization interacts with AI, including model governance, tooling, infrastructure, and integration frameworks. Collaborating with stakeholders across Sales, Product, Engineering, and Revenue Operations to embed AI capabilities into workflows, products, and commercial strategies. Driving innovation in Generative AI, Agentic AI, deep learning, and large scale ML deployment. Championing best practice in MLOps, cloud native development (Azure preferred), and scalable production deployment. Presenting AI program outcomes, strategic recommendations, and technical guidance to senior leadership and executive audiences. What you will need Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or related field (required). Master's or PhD in AI/ML, Computer Science, or related discipline (preferred). 8+ years of experience in AI/ML engineering, applied machine learning, or advanced analytics. Demonstrated experience leading technical AI teams and delivering enterprise scale AI/ML solutions. Deep expertise in machine learning algorithms, neural networks, large scale architectures, and modern AI frameworks. Hands on experience with Generative AI and Agentic AI (LLMs, foundation models, autonomous agents, large scale inference). Strong proficiency in Python and SQL; experience building production grade ML systems. Experience with Azure or another major cloud platform; familiarity with MLOps pipelines and deployment automation. Excellent communication skills and the ability to simplify complex technical concepts for business audiences. Ability to thrive in a fast paced, high impact environment with multiple stakeholders. Curiosity, proactive problem solving mindset, and passion for innovation. What we offer you Opportunities to innovate in fintech and shape the future of enterprise AI. Inclusive and diverse team atmosphere. Professional and personal development. Resources to contribute to your community. Competitive salary and benefits. FIS Global

Job Title: Junior Data Scientist Job Family: Business Operations Reports To: Lead Data Scientist Subordinates: None Company Overview Eastnets is a leading player in the B2B fintech industry. We are a global provider of compliance and payments solutions for the financial services sector. Our experience and expertise help ensure trust at over 800 financial institutions across the world, including 11 of the top global banks. We secure institutions from financial crime by helping our partners manage risk through sanction screening, transaction monitoring, analytics, and reporting, along with market-leading consultancy and customer support. The Junior Data Scientist is responsible for problem-solving across multiple domains; Fraud, Financial Crime & Compliance Risk business of Eastnets. This is an all-encompassing role that will involve: business requirements gathering and understanding, ideas generation, data engineering, model development and visualization, model deployment/dev ops, model management, stakeholder management, and model interpretation to relevant business owners. He/She will use technology and framework for development, using Python, and have a chance to shape solutions within a continuously evolving industry. The candidate will contribute to customer demos, and requests for proposals and interact with Product Owners and Sales support. Key Responsibilities Use machine learning, modeling, analytics and statistical and mathematical techniques to solve problems. Extract data from multiple sources, exploratory data analysis, plots/charts, etc. Propose solutions and strategies to business challenges. Represent Eastnets at external events such as webinars, conferences. Build strategic relationships with Product Owners, Sales and Customers. Research new and emerging technologies, tools and techniques. Curiosity in solving problems using a novel machine learning approach. Educate other team members, Product Managers, Developers, and QA on data science techniques used to solve the problem at hand. Responsible for managing multiple data science projects simultaneously. Gather requirements from relevant stakeholders and manage expectations. Coordinate with developers and QA on deploying developed models. Maintain the security of the information, devices and systems that Eastnets and its personnel, customers and partners use. Protect Eastnets business information and any customer, supplier or partner information within its custody by safeguarding its confidentiality, integrity and availability. Adhere to and comply with Eastnets internal security policies, Code of Ethics, Non-Disclosure Policy, Non-Compete Policy, Email Policy, Proprietary Rights Acknowledgement, Background Check Policy, and all other internal policies and employee handbook. Participate in the company's wide initiatives. Requirements Graduate preferably in a STEM subject. An MBA or equivalent post-graduate qualification is a plus. Data science certifications would be a plus. Strong experience in programming. (Any mainstream data science programming language). Familiarity with AI/ML concepts and their application in financial crime prevention is a strong plus. Solid knowledge in data science methodology e.g. supervised learning, clustering, forecasting and time series analysis, text analytics and natural language processing, etc. Solid knowledge in machine learning and statistical techniques: regression, neural networks, social network analysis, support vector machine, etc. Proficiency in SQL. Experience in delivering product solutions in Fraud, Financial Crime and Compliance is a plus. Experience in Natural Language Processing, the financial sector, financial service providers, and the banking sector is a plus. Experience in developing solutions using advanced technologies such as Artificial Intelligence in financial services and products. Excellent analytical skills with the ability to integrate diverse and complex data problems. Flexible attitude with proven experience of working in a small and agile team. Must be a team player. Strong relationship management skills with a proven ability to work across the business. Excellent communication skills for different internal and external communication needs. Knowledge in AI technologies and their application. Apply for this role and join the Eastnets family Fill out the form, send your CV to and our recruitment team will be in touch if your skill set matches our needs.

One of the UK's fastest-growing fintechs is hiring. At ANNA Money, we're rethinking what business admin should feel like for freelancers, founders and small businesses. No jargon, no clunky tools - just smart, intuitive products that actually save people time. From invoicing and expenses to tax and accounting, we're building a platform that removes the hassle from running a business. Powered by AI and backed by genuinely brilliant customer support, ANNA helps thousands of customers focus less on admin and more on what they do best. Our Vision:ANNA Money endeavours to alleviate the burden of time-consuming administrative tasks that every small business owner inevitably encounters. Our core objective is to automate these repetitive tasks, enhancing our customers' efficiency, speed, and overall ease. This dedication to automation supports our customers' business operations and allows them the freedom to dedicate time to other critical aspects of their business. Our Team:Globally, ANNA Money boasts a diverse team of approximately 150 professionals, primarily consisting of adept software developers and innovative data scientists dedicated to advancing our product offerings. Presently, over 100,000 customers trust ANNA for their banking and administrative needs. Our Approach:We pride ourselves on remaining at the forefront of technological advancements, employing a modern technical stack and methodologies that enable us to deploy code to production an impressive 750 times per month. Join Us:If you're driven by innovation, hold a passion for creating impactful solutions, and are looking for an opportunity to contribute to the revolutionising of business administration for freelancers and small businesses across the UK, ANNA Money is your platform to thrive. Together, let's transform the way businesses approach admin and banking - making it smarter, faster, and more efficient for everyone. Explore career opportunities with us and become a key player in shaping the future of business administration. Our Technology Stack Python (aiohttp, sqlalchemy) TypeScript (React, MobX) Flutter/Dart PostgreSQL/MongoDB RabbitMQ Kubernetes What You'll Do Hands-on coding to solve complex problems with a focus on defensive programming, resilience, and performance Own technical solution design for significant product features, software modules, and technical initiatives Demonstrate self-guided problem-solving abilities to create robust technical solutions for vague business requirements Take initiative to course-correct projects when they deviate from their intended path Collaborate with a cross-functional team of engineers, product managers, UX designers, and mobile developers to build new features Write unit and integration tests alongside production code to ensure reliable and scalable features Contribute to regular planning sessions such as refinement and task prioritisation Take ownership of your code from inception to deployment into Production, following a continuous delivery model. Get involved in live incidents as required, following the internal incident management process Support, coach, and mentor other team members, setting high standards and continually improving processes Provide technical support to internal teams and actively share knowledge through documentation Initiate and contribute to broader engineering technical designs Staying abreast of and (where necessary) applying the latest emerging technologies Experience developing software in one or more programming languages from the list (Python, Java, C#, Go) 7+ years of software engineering experience in an industrial setting Experience with data structures or algorithms Experience building distributed systems Excellent verbal communication skills. Good problem-solving skills. Team player. Experience with UI/UX Preferred qualifications Proficiency in Python with experience in asynchronous frameworks (aiohttp, fastapi, etc) Experience with Docker, Kubernetes, Helm Experience with RabbitMQ, PostgreSQL, MongoDB Experience with Flutter/Dart Visa sponsorship costs For Skilled Worker Visa sponsorship, ANNA covers all costs we are legally required to pay as your sponsoring employer - this includes theCertificate of Sponsorship (CoS)fee and theImmigration Skills Charge (ISC). Candidates are responsible for their ownvisa application feeandImmigration Health Surcharge (IHS), which are payable directly to the UK Home Office as part of the visa application process. You can find more details about these costs on the UK Government website: UK Skilled Worker Visa - How much it costs What We Offer At ANNA, we celebrate a flat organisational structure. You might be wondering what that means! Well, it's all about empowering our team by sharing power and decision making responsibilities, so everyone can feel a sense of ownership. Life at ANNA (flexible by design) Flexible working - focused on trust, autonomy and outcomes Hybrid or Remote working, depending on role Work from anywhere for up to 3 months Support towards home working equipment Flexible hours for caregiving responsibilities Temporary reduced hours / phased returns when life needs it Time off for your child's first day of school (non negotiable ) Employee Growth Share options - because when ANNA grows, you grow too Wellbeing (because you're a human first) ️ Trained Mental Health First Aiders Perkbox EAP + counselling support Online GP access & prescription service ️ Bupa private medical insurance On demand wellness content Menopause support (policy + practical adjustments that actually help) Financial Wellbeing (money matters - we're ANNA after all) Salary sacrifice pension contributions Workplace nursery salary sacrifice ️ Perkbox discounts & reward points Cycle to Work scheme Salary sacrifice for Home & Tech (coming April '26) Growth & Self Direction (invest in you) ️ £1k annual personal travel allowance £1k annual personal learning allowance (including non-work learning - yes, really) Time Off & Life Moments (the important stuff) Enhanced parental leave Adoption leave Pregnancy loss & compassionate family leave Emergency dependent leave Belonging & Connection (we actually like each other) Monthly team brunches Regular team building events Free drinks & snacks in the office Please note that due to a high level of demand in candidates for this role, we're unable to respond to individual emails or questions about the position. We hope that we've been thorough and transparent regarding the requirements and expectations of this role.

We are building the financial system for the next century. One where control sits in the hands of customers - not banks. Where money moves on rails that are faster, smarter, and radically more efficient. Where wealth management tools help you grow your savings for decades - and build generational wealth. Where fewer intermediaries mean more value stays where it belongs: in our customers' pockets. We operate with long-term ambition and absolute conviction. We are not here to iterate on the past - we are here to redesign it. This is a defining moment to join us. We are building what we believe will become one of the most important financial institutions in the world. That requires exceptional talent, relentless standards, and people who care deeply about the work. At ARQ, we are turning the financial system upside down - starting in the Americas. We are nimble, but ambitious. We move fast, learn fast, and innovate relentlessly. Technology is our greatest ally, and execution is our edge. We build as a team. We think long term. We aim for world class in everything we do. If you are exceptional at what you do - and ready to help redefine finance - we'd love to meet you.Are you ready to build what comes next? About the team We believe that small teams with the best talent outcompete massive companies with mediocre capabilities. That's why we have gathered a set of people who have done it before at iconic companies like Revolut, Uber, Amazon, Block and UBS: we owned some of the most loved and profitable products, delivered top notch transaction processing platforms, created beautiful mobile applications - and helped them become profitable companies that changed the lives of millions of people. In our quest to reshape the global financial system we have raised tens of millions of dollars from leading investors like Sequoia Capital, Founders Fund, Brevan Howard Digital, Y Combinator and Kaszek Ventures. Data Analyst - London Location London Employment Type Full time Location Type Hybrid Department What we're looking for Are you curious about how things work and motivated by uncovering insights hidden in data? As a Data Analyst at ARQ, you'll help us understand our business, customers, and operations through rigorous analysis and thoughtful storytelling. You'll explore data, detect patterns, and build the foundations for decisions that shape the future of our products and company. This is a role for someone early in their analytics career who wants to grow - learning how data drives product, financial, and strategic decisions in a fast paced fintech environment. What you'll be doing Explore and Analyze Data: Investigate user behavior, performance trends, and key metrics to uncover what's driving changes. Identify Anomalies and Opportunities: Spot unusual patterns or spikes and help the team understand their root causes. Reporting & Automation: Build and maintain dashboards and automated reports that make data accessible and reliable. Decision Support: Translate analytical findings into clear recommendations for product and operational improvements. Metric Design: Help define and refine the KPIs that matter most for our business and customer experience. Documentation: Keep analyses, methodologies, and assumptions well documented and reproducible. Modeling & Experimentation: Contribute to basic modeling tasks and structured experiments under guidance from senior analysts or data scientists. Continuous Learning: Expand your analytical toolkit and develop product sense through real world problem solving and mentorship. What you'll need 1-3 years of experience in analytics, data, or operations (internships count) Strong SQL skills for querying and exploring datasets Comfortable reading code and writing basic Python scripts for data manipulation, automation, and analysis Experience contributing to a shared analytics codebase or modern data stack (e.g., Snowflake/BigQuery + dbt + Git workflow) Analytical curiosity and a structured approach to problem solving Good communication skills - able to explain insights clearly and visually Initiative to automate repetitive tasks and improve reporting workflows Interest in fintech, data driven decision making, and machine learning concepts Ambitious, high potential mindset with evidence of strong achievement, fast progression, or outstanding academic/professional performance Nice to have STEM degree preferred (e.g., Mathematics, Computer Science, Engineering, Physics, Economics, or related fields) Experience with BI or visualization tools (Metabase, Looker, etc.) Familiarity with dbt for building and maintaining data models, writing tests, and managing transformations Exposure to fraud, financial, or product analytics (any domain welcome) Spanish/Portuguese proficiency for internal and external communications. Own the development process that will face on the customer's impact Latest technology to work with Strong team that will help you improve your skills.

Lenkie is a fast-growing UK SME lender on a mission to give small businesses access to fair, fast, and flexible finance. We're at an exciting inflection point - scaling our lending book and building the data infrastructure that will power our credit decisions for years to come. This is a rare opportunity to be the foundational data science hire and have a genuine hand in shaping how we think about credit risk, model development, and data-driven decisioning in risk as well as other parts of the business. About the job We're looking for a (Senior) Data Scientist with deep credit risk experience to join us as one of our earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up - from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values. This isn't a role where you'll plug into an existing machine. You'll be defining how we do things, building the infrastructure, and helping recruit the team around you as we grow. Key Responsibilities Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams Work with Open Banking, bureau, and alternative data sources to enrich our credit assessment Define data science best practices, tooling, and ways of working as the function grows Partner closely with Product, Engineering, and Credit to translate business problems into data solutions Support the Head of Credit and Credit Risk Manager on strategic projects - limit setting, pricing, risk appetite calibration Use your data science expertise for projects outside of credit risk, e.g. Customer Lifetime Value modeling. Qualifications/Required Skills 2-5 years of experience in data science or quantitative analysis, with a strong focus on credit risk in a fintech or lending environment Hands-on experience building credit scorecards or risk models (application, behavioural, or collections) Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.) Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources Comfort working in small, fast-moving teams where you have to be both strategic and hands-on Experience with SME lending is a strong plus (vs. consumer) Strong communicator - able to explain model outputs and data insights to non-technical stakeholders How we reward performance Be a founding member of the data team with real ownership and influence Competitive salary + meaningful equity Hybrid working from our London office A mission you can get behind - helping small businesses access the finance they deserve We're building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate based on age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.

Job Overview We know that people want great value combined with an excellent experience from a bank they can trust, so we launched our digital bank, Chase UK, to revolutionise mobile banking with seamless journeys that our customers love. We're already trusted by millions in the US and we're quickly catching up in the UK - but how we do things here is a little different. We're building the bank of the future from scratch, channelling our start up mentality every step of the way - meaning you'll have the opportunity to make a real impact. As a Lead Machine Learning Scientist at JPMorgan Chase within the International Consumer Bank, you will be a part of a flat structure organization. Your responsibilities are to deliver end to end cutting edge solutions in the form of cloud native microservices architecture applications leveraging the latest technologies and the best industry practices. You are expected to be involved in the design and architecture of the solutions while also focusing on the entire SDLC lifecycle stages. Our Machine Learning team is at the heart of this venture, focused on getting smart ideas into the hands of our customers. We're looking for people who have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By their nature, our people are also solution oriented, commercially savvy and have a head for fintech. We work in tribes and squads that focus on specific products and projects - and depending on your strengths and interests, you'll have the opportunity to move between them. Job Specification Job responsibilities: Lead the development and maintenance of machine learning models to solve complex business problems Develop the technical skills of junior colleagues through mentorship and training Collaborate with cross functional teams to identify opportunities for leveraging data to drive business solutions Analyse large, heterogenous datasets to extract actionable insights and inform decision making Stay updated with the latest advancements in machine learning and especially Large Language Models and agentic systems Identify the right state of the art solutions for the bank's objectives and manage colleagues to implement them as clean, production ready code Communicate findings and recommendations through clear and concise reports and presentations Required qualifications, capabilities and skills: Experience leading teams to deliver production machine learning solutions Proficiency in Python and SQL and familiarity with good software engineering practices Excellent written and verbal communication Strong experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit learn Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus Collaborative, humble and enthusiastic attitude Preferred qualifications, capabilities and skills: Experience deploying on AWS cloud infrastructure using Lambda, Glue, S3 etc. Experience in deep neural networks and familiarity with the latest developments in related fields Experience in LLM model finetuning and continuous learning techniques Experience in prompt engineering techniques and state of the art LLM architectures

JPMorgan Chase & Co. is seeking a Lead Machine Learning Scientist to deliver innovative machine learning solutions within the International Consumer Bank. You will lead a team to develop and maintain models, collaborating across teams to leverage data for business solutions. Candidates should be skilled in Python and SQL, comfortable with frameworks like TensorFlow and have a solid grasp of mathematical concepts. The position demands a collaborative spirit and a passion for technology and fintech, with opportunities to work on advanced machine learning applications.

Hello! We're Teya. Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance. At Teya we believe small, local businesses are the lifeblood of our communities. We're here because we don't believe there's a level playing field that gives small businesses with a fighting chance against the giants of the high street. We're here because we see banks and legacy service providers making things harder for them. We don't think the best technology or the best service should be reserved for those with the biggest headquarters. We're here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us. Become a part of our story. We're looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits. The Role We are looking for a Senior Credit Data Analyst to lead our data strategy within the Credit Product team. You will be responsible for the full data lifecycle - from designing robust dbt models to delivering insights that drive SMB lending decisions. You will work closely with Credit, Product, and Engineering teams to ensure our credit products are optimized, scalable, and supported by high-integrity data. Key Responsibilities Data Leadership Lead the credit business with data-driven solutions Own the roadmap for credit reporting and analytics from inception to delivery Modelling & Architecture Design, implement, and maintain scalable data models in dbt Ensure the Data Warehouse remains a reliable "source of truth" for credit performance Stakeholder Management Partner with business leads to gather requirements Translate complex raw data into well-structured data models and clear reports Self Service Growth Develop and maintain Tableau dashboards Promote a data-driven culture by enabling non technical stakeholders to interpret insights independently Optimization & Analysis Analyze external customer data (Credit Bureau, Companies House) alongside internal business data Improve risk assessment and product conversion performance Data Quality Maintain high data quality standards across the lifecycle Collaborate with Data Engineers to ensure reporting requirements are aligned with product implementation Must Have Requirements 3+ years' experience in a data related role (ideally within FinTech or Lending) Strong proficiency in SQL Strong experience with Tableau (or equivalent BI tool) Proven experience with dbt and data modelling in cloud environments (Snowflake, Redshift) Strong understanding of ETL processes Experience collaborating with Data Engineers on production pipelines Proficiency using Git for version control Strong analytical skills with ability to translate technical findings into business conclusions Self starter attitude, comfortable in fast paced environments Nice to Have Direct experience in SMB lending or Credit products Experience working with Credit Data Scientists (building datasets for lending funnel analysis or predictive modelling) Experience handling Credit Bureau data (Experian/Equifax) Experience working with Companies House data Proficiency in Python for data manipulation Exposure to Machine Learning The Perks Flexible working hours built on trust and collaboration Physical and mental health support through Wellhub, including access to 1,500+ gyms, 1 1 therapy, meditation, and wellbeing apps Enhanced maternity and paternity leave Cycle to Work Scheme Health and Life Insurance Pension Scheme 25 days of annual leave (+ bank holidays) Daily office snacks Friendly, informal office environment in Central London Teya is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all. If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application-we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.